



'''simple docstring'''



from collections import OrderedDict
from typing import TYPE_CHECKING, Any, List, Mapping, Optional, Union

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import TensorType, logging


if TYPE_CHECKING:
							from ...onnx.config import PatchingSpec
							from ...tokenization_utils_base import PreTrainedTokenizerBase


lowerCAmelCase_  :							Union[str, Any]             =    logging.get_logger(__name__)

lowerCAmelCase_  :							Tuple             =    {
    'allenai/longformer-base-4096': 'https://huggingface.co/allenai/longformer-base-4096/resolve/main/config.json',
    'allenai/longformer-large-4096': 'https://huggingface.co/allenai/longformer-large-4096/resolve/main/config.json',
    'allenai/longformer-large-4096-finetuned-triviaqa': (
        'https://huggingface.co/allenai/longformer-large-4096-finetuned-triviaqa/resolve/main/config.json'
    ),
    'allenai/longformer-base-4096-extra.pos.embd.only': (
        'https://huggingface.co/allenai/longformer-base-4096-extra.pos.embd.only/resolve/main/config.json'
    ),
    'allenai/longformer-large-4096-extra.pos.embd.only': (
        'https://huggingface.co/allenai/longformer-large-4096-extra.pos.embd.only/resolve/main/config.json'
    ),
}
class 						lowerCamelCase_				(       snake_case_      ):
						_lowerCAmelCase  : Dict						  =					'longformer'







						def __init__(	self :   List[Any]					,     lowerCAmelCase__ :   Union[List[int], int] = 5_12					,     lowerCAmelCase__ :   int = 2					,     lowerCAmelCase__ :   int = 1					,     lowerCAmelCase__ :   int = 0					,     lowerCAmelCase__ :   int = 2					,     lowerCAmelCase__ :   int = 3_05_22					,     lowerCAmelCase__ :   int = 7_68					,     lowerCAmelCase__ :   int = 12					,     lowerCAmelCase__ :   int = 12					,     lowerCAmelCase__ :   int = 30_72					,     lowerCAmelCase__ :   str = "gelu"					,     lowerCAmelCase__ :   float = 0.1					,     lowerCAmelCase__ :   float = 0.1					,     lowerCAmelCase__ :   int = 5_12					,     lowerCAmelCase__ :   int = 2					,     lowerCAmelCase__ :   float = 0.02					,     lowerCAmelCase__ :   float = 1e-12					,     lowerCAmelCase__ :   bool = False					,     **lowerCAmelCase__ :   Any					,     ):

													"""simple docstring"""
													super().__init__(pad_token_id=lowerCAmelCase__					,     **lowerCAmelCase__					)

													SCREAMING_SNAKE_CASE       :   Optional[int]         =      attention_window
													SCREAMING_SNAKE_CASE       :   Union[str, Any]         =      sep_token_id
													SCREAMING_SNAKE_CASE       :   Union[str, Any]         =      bos_token_id
													SCREAMING_SNAKE_CASE       :   Union[str, Any]         =      eos_token_id
													SCREAMING_SNAKE_CASE       :   Any         =      vocab_size
													SCREAMING_SNAKE_CASE       :   Optional[int]         =      hidden_size
													SCREAMING_SNAKE_CASE       :   List[Any]         =      num_hidden_layers
													SCREAMING_SNAKE_CASE       :   Any         =      num_attention_heads
													SCREAMING_SNAKE_CASE       :   Dict         =      hidden_act
													SCREAMING_SNAKE_CASE       :   Dict         =      intermediate_size
													SCREAMING_SNAKE_CASE       :   Tuple         =      hidden_dropout_prob
													SCREAMING_SNAKE_CASE       :   Any         =      attention_probs_dropout_prob
													SCREAMING_SNAKE_CASE       :   Dict         =      max_position_embeddings
													SCREAMING_SNAKE_CASE       :   int         =      type_vocab_size
													SCREAMING_SNAKE_CASE       :   Union[str, Any]         =      initializer_range
													SCREAMING_SNAKE_CASE       :   Any         =      layer_norm_eps
													SCREAMING_SNAKE_CASE       :   List[Any]         =      onnx_export


class 						lowerCamelCase_				(       snake_case_      ):







						def __init__(	self :   Tuple					,     lowerCAmelCase__ :   "PretrainedConfig"					,     lowerCAmelCase__ :   str = "default"					,     lowerCAmelCase__ :   "List[PatchingSpec]" = None					):

													"""simple docstring"""
													super().__init__(lowerCAmelCase__					,     lowerCAmelCase__					,     lowerCAmelCase__					)
													SCREAMING_SNAKE_CASE       :   List[str]         =      True







						@property
						def        __lowercase     (	self :   int					):

													"""simple docstring"""
													if self.task == "multiple-choice":
																				SCREAMING_SNAKE_CASE       :   str         =      {0: '''batch''', 1: '''choice''', 2: '''sequence'''}
													else:
																				SCREAMING_SNAKE_CASE       :   Dict         =      {0: '''batch''', 1: '''sequence'''}
													return OrderedDict(
													    [
													        ('''input_ids''', dynamic_axis),
													        ('''attention_mask''', dynamic_axis),
													        ('''global_attention_mask''', dynamic_axis),
													    ]					)







						@property
						def        __lowercase     (	self :   List[str]					):

													"""simple docstring"""
													SCREAMING_SNAKE_CASE       :   Union[str, Any]         =      super().outputs
													if self.task == "default":
																				SCREAMING_SNAKE_CASE       :   Tuple         =      {0: '''batch'''}
													return outputs







						@property
						def        __lowercase     (	self :   Optional[int]					):

													"""simple docstring"""
													return 1e-4







						@property
						def        __lowercase     (	self :   Optional[int]					):

													"""simple docstring"""
													# needs to be >= 14 to support tril operator
													return max(super().default_onnx_opset					,     14					)







						def        __lowercase     (	self :   int					,     lowerCAmelCase__ :   "PreTrainedTokenizerBase"					,     lowerCAmelCase__ :   int = -1					,     lowerCAmelCase__ :   int = -1					,     lowerCAmelCase__ :   bool = False					,     lowerCAmelCase__ :   Optional[TensorType] = None					,     ):

													"""simple docstring"""
													SCREAMING_SNAKE_CASE       :   Optional[int]         =      super().generate_dummy_inputs(
													    preprocessor=lowerCAmelCase__					,     batch_size=lowerCAmelCase__					,     seq_length=lowerCAmelCase__					,     is_pair=lowerCAmelCase__					,     framework=lowerCAmelCase__					)
													import torch

													# for some reason, replacing this code by inputs["global_attention_mask"] = torch.randint(2, inputs["input_ids"].shape, dtype=torch.int64)
													# makes the export fail randomly
													SCREAMING_SNAKE_CASE       :   Dict         =      torch.zeros_like(inputs['''input_ids''']					)
													# make every second token global
													SCREAMING_SNAKE_CASE       :   Dict         =      1

													return inputs









'''simple docstring'''



from queue import PriorityQueue
from typing import Any

import numpy as np
def        UpperCAmelCase (    A	:					dict       ,		A	:					str       ,		A	:					set       ,		A	:					set       ,		A	:					dict       ,		A	:					dict       ,		A	:					PriorityQueue       ,		A	:					dict       ,		A	:					float | int       ,		):
							for nxt, d in graph[v]:
														if nxt in visited_forward:
																					continue
														SCREAMING_SNAKE_CASE       :   str         =      cst_fwd.get(A       ,		np.inf					)
														SCREAMING_SNAKE_CASE       :   Optional[int]         =      cst_fwd[v] + d
														if new_cost_f < old_cost_f:
																					queue.put((new_cost_f, nxt)					)
																					SCREAMING_SNAKE_CASE       :   Tuple         =      new_cost_f
																					SCREAMING_SNAKE_CASE       :   List[str]         =      v
														if nxt in visited_backward:
																					if cst_fwd[v] + d + cst_bwd[nxt] < shortest_distance:
																												SCREAMING_SNAKE_CASE       :   Union[str, Any]         =      cst_fwd[v] + d + cst_bwd[nxt]
							return shortest_distance
def        UpperCAmelCase (    A	:					str       ,		A	:					str       ,		A	:					dict       ,		A	:					dict					):
							SCREAMING_SNAKE_CASE       :   Dict         =      -1

							SCREAMING_SNAKE_CASE       :   Optional[int]         =      set()
							SCREAMING_SNAKE_CASE       :   Optional[Any]         =      set()
							SCREAMING_SNAKE_CASE       :   Any         =      {source: 0}
							SCREAMING_SNAKE_CASE       :   Tuple         =      {destination: 0}
							SCREAMING_SNAKE_CASE       :   Union[str, Any]         =      {source: None}
							SCREAMING_SNAKE_CASE       :   Optional[int]         =      {destination: None}
							SCREAMING_SNAKE_CASE       :   PriorityQueue[Any]         =      PriorityQueue()
							SCREAMING_SNAKE_CASE       :   PriorityQueue[Any]         =      PriorityQueue()

							SCREAMING_SNAKE_CASE       :   List[str]         =      np.inf

							queue_forward.put((0, source)					)
							queue_backward.put((0, destination)					)

							if source == destination:
														return 0

							while not queue_forward.empty() and not queue_backward.empty():
														SCREAMING_SNAKE_CASE       ,SCREAMING_SNAKE_CASE       :   str         =      queue_forward.get()
														visited_forward.add(A					)

														SCREAMING_SNAKE_CASE       ,SCREAMING_SNAKE_CASE       :   int         =      queue_backward.get()
														visited_backward.add(A					)

														SCREAMING_SNAKE_CASE       :   Tuple         =      pass_and_relaxation(
														    A       ,		A       ,		A       ,		A       ,		A       ,		A       ,		A       ,		A       ,		A       ,		)

														SCREAMING_SNAKE_CASE       :   Optional[int]         =      pass_and_relaxation(
														    A       ,		A       ,		A       ,		A       ,		A       ,		A       ,		A       ,		A       ,		A       ,		)

														if cst_fwd[v_fwd] + cst_bwd[v_bwd] >= shortest_distance:
																					break

							if shortest_distance != np.inf:
														SCREAMING_SNAKE_CASE       :   int         =      shortest_distance
							return shortest_path_distance


lowerCAmelCase_  :							int             =    {
    'B': [['C', 1]],
    'C': [['D', 1]],
    'D': [['F', 1]],
    'E': [['B', 1], ['G', 2]],
    'F': [],
    'G': [['F', 1]],
}
lowerCAmelCase_  :							str             =    {
    'B': [['E', 1]],
    'C': [['B', 1]],
    'D': [['C', 1]],
    'F': [['D', 1], ['G', 1]],
    'E': [[None, np.inf]],
    'G': [['E', 2]],
}

if __name__ == "__main__":
							import doctest

							doctest.testmod()




